Upload
others
View
13
Download
0
Embed Size (px)
Citation preview
INFOTECH OULU Annual Report 2016 1
BIOMIMETICS AND INTELLIGENT SYSTEMS GROUP (BISG)
Professor Juha Röning and Dr. Heli Koskimäki, Biomimetics and Intelligent Systems Research Unit, Faculty
of Information Technology and Electrical Engineering, and Professor Seppo Vainio, Oulu Center for Cell-
Matrix Research, Faculty of Biochemistry and Molecular Medicine, University of Oulu
juha.roning(at)oulu.fi, heli.koskimaki(at)oulu.fi, seppo.vainio(at)oulu.fi
http://www.oulu.fi/bisg
Background and Mission
Biomimetics and Intelligent Systems Group (BISG) is
a fusion of expertise from the fields of computer sci-
ence and biology. In BISG, our basis are intelligent
systems and our research areas include data mining,
machine learning, robotics, and information security.
More precise research topics vary from data mining
algorithm development and optimization of industrial
manufacturing processes all the way to environmental
monitoring with mobile robots.
Bringing expertise from ICT and Biotech together, we
will reach the skills to make use of the mechanisms
common in information processing and the biological
data processing system and extrapolate this to intelli-
gent solution making in ICT. One important goal of
this program is to be able to physically link living cells
via identified signaling systems to establish learning
complex that involves Bio and ICT in a unified bifunc-
tional interactive machine.
The group consists of four sub-groups: Data Analysis
and Inference Group, Organ BioEngineering Biology,
Robotics and Secure Programming
We have conducted basic research in intelligent sys-
tems and tissue engineering for over ten years as indi-
vidual groups. Now we have joint our efforts. Our team
consists of 2 professors, 10 post-doctoral researchers
and 15 doctoral students. The annual external funding
of the group is more than two million Euros, in addi-
tion to our basic university funding. In the reported
year, there have been 23 completed doctoral degree
from the group. From the research of the group, 11
spin-off companies have been established so far:
Codenomicon, Clarified Networks, Hearth Signal,
Nose Laboratory, Nelilab, Atomia, Indalgo Probot,
Aquamarine Robots, Radai and IndoorAtlas.
We co-operate with many international and domestic
partners. In applied research, we are active in European
projects. In addition, several joint projects are funded
by the Finnish Funding Agency for Technology and
Innovation (Tekes) and industry. We were a research
partner in the SIMP and CyberTrust SHOKs. Prof.
Juha Röning was selected as ACO (Academic coordi-
nator) of the Cyber Trust program.
We are active in the scientific community. For exam-
ple, Prof. Juha Röning is acting as visiting professor of
Tianjin University of Technology and as the Robot
Science Adviser of Tianjin Science and Technology
Center for Juveniles. He served as a member of the
Board of Directors in euRobotics and as a member of
the SAFECode International Board of Advisors. He
chaired the euRathlon / TRADR Summer School 2016
in Oulu, Finland, 22nd to 26th of August. It was a five-
day course to provide participants with a full overview
and hands-on experience with multi-domain real robot-
ic systems. He also chaired with prof. Othmane the
First International Workshop on Agile Development of
Secure Software (ASSD’16) in Salzburg 1st of Sep-
tember. With robotics group, he participated
NORDRUM project where aim was to collect radiation
data from the environment using an unmanned aerial
vehicle (UAV). The testing area was located in Nor-
way, Hauerseter Leir military campsite (5th to 7th of
September).
During the reporting year, the group organized the 9th
International Crisis Management Workshop and Winter
School (CrIM’16) and NordSec conference which
brought together both Finnish and international infor-
mation security experts. The group also organized
Summer School 2016 of Data mining, big data and
open data together with Exactus DP and Aurora DP
15th to 19th of August.
Representing Finland as a Partner for Peace (PfP) na-
tion, BISG / Prof. Röning participated the Specialists’
Meeting on Intelligence and Autonomy in Robotics,
held in Wachtberg, Bonn, Germany on 25 – 27 October
2016.
Celentano and Röning are co-editors, together with
collaborating partners, of an IEEE Access special sec-
tion on Recent Advances in Socially-aware Mobile
Networking.
Prof. Seppo Vainio has been the chair in the Minisym-
posium ”Omics in Biomedicine” (2016). He is also part
of a European nanotechnology ”HyNanoDend” net-
work.
Scientific Progress
Intelligent Systems Incorporating Security
Within the Biomimetics and Intelligent Systems Group,
the Oulu University Secure Programming Group
(OUSPG) has continued research on security and safety
in intelligent systems. Security and safety challenges in
INFOTECH OULU Annual Report 2016 2
intelligent systems are threefold: increasing complexity
leads to unforeseeable failure modes, quality is not the
priority and awareness is lacking. We have approached
the challenges from these three directions in our re-
search.
Complexity - Model Inference and Pattern Recogni-
tion: we work under the premises of unmanageable
growth in software and system complexity and emer-
gent behaviour (unanticipated, not designed) having a
major role in any modern non-trivial system. We have
worked on natural science approaches to understanding
artificial information processing systems. We have
developed and applied model inference and pattern
recognition to both content and causality of signalling
between different parts of systems.
Quality - Building Security In: software quality prob-
lems, wide impact vulnerabilities, phishing, botnets,
and criminal enterprise have proven that software and
system security is not just an add-on, despite the past
focus of the security industry. Instead, security, trust,
dependability and privacy have to be considered over
the whole life-cycle of the system and software devel-
opment, from requirements all the way to operations
and maintenance. This is furthermore emphasized by
the fact that large intelligent systems are emergent and
do not follow a traditional development life-cycle.
Building security in not only makes us safer and se-
cure, but also improves overall system quality and
development efficiency. Security and safety are trans-
formed from inhibitors to enablers. We have developed
and applied black-box testing methods to set quantita-
tive robustness criteria. International recognition of the
Secure Development Life Cycle has provided us with a
way to map our research on different security issues.
Awareness - Vulnerability Life Cycle: Intelligent sys-
tems are born with security flaws and vulnerabilities,
new ones are introduced, old ones are eliminated. Any
deployment of system components comes in genera-
tions that have different sets of vulnerabilities. Tech-
nical, social, political and economic factors all affect
this process. We have developed and applied processes
for handling the vulnerability life-cycle. This work has
been adopted in critical infrastructure protection.
Awareness of vulnerabilities and the processes to han-
dle them all increase the survivability of emergent
intelligent systems for developers, users and society.
These research goals are reached through a number of
research activities.
Secure Software Development Lifecycle as a part of
the Cyber Trust project - we approach all three goals
by researching practical ways of building security into
Secure Platforms, Cloud Computing services and Criti-
cal Infrastructure, from the design phase to actual oper-
ational use (Figure 1).
Figure 1. Dependencies of a single cloud based web service visualized by technology and location.
Situational Awareness in Information and Cyber Secu-
rity aims to understand critical environments and accu-
rately predict and respond to potential problems that
might occur. Networked systems and networks have
vulnerabilities that present significant risks to both
individual organizations and critical infrastructure. By
anticipating what might happen to these systems, lead-
ers can develop effective countermeasures to protect
their assets (Figure 2).
Figure 2. Port scanning visualized in an industrial auto-mation network.
Coverage based robustness testing: Modern web
browsers are feature rich software applications availa-
ble for different platforms ranging from home comput-
ers to mobile phones and modern TVs. Because of this
variety, the security testing of web browsers is a di-
verse field of research. Previously, we have found a
number of bugs in browsers, but previous methods
were seeing diminishing returns. By utilizing code
coverage we were able to improve on existing state of
the art. This work introduces a cross-platform testing
harness for robustness testing, called CovFuzz. In the
design of CovFuzz, test case generators and instrumen-
tation are separated from the core into separate mod-
ules. This allows the user to implement feature specific
test case generators and platform specific instrumenta-
tions, and to execute those in different combinations.
Identification of a protocol gene: This research, PRO-
TOS-GENOME, approaches the problems of com-
plexity and quality by developing tools and techniques
for reverse-engineering, and identification of protocols
based on using protocol genes - the basic building
INFOTECH OULU Annual Report 2016 3
blocks of protocols. The approach is to use techniques
developed for bioinformatics and artificial intelligence.
Samples of protocols and file formats are used to infer
structure from the data. This structural information can
then be used to effectively create large numbers of test
cases for this protocol.
OUSPG Open: This activity brought together over 60
people from 23 academic and commercial organiza-
tions by organizing regular events throughout the
summer. Five novel security tools were produced as
collaborative projects. For example, TryTLS, a tool for
the software and library developers, vulnerability re-
searchers, and end-users, who want to use TLS safely,
resulted in a number of issues being found in common-
ly used programming libraries.
Privacy and Security and Online Social Networks:
Exploiting Social Structure for Cooperative Mobile
Networking (SOCRATE), a two -year (2015-2016)
Tekes funded project under the Wireless Innovation
between Finland and U.S. programme WiFiUS
[http://wifius.org/], is a collaboration between the Uni-
versity of Oulu (co-PI Dr Ulrico Celentano), VTT,
Aalto University, Arizona State University, and Uni-
versity of Nevada, supported by NSF funding on the
US side. BISG contribution focused on privacy and
security issues in online social networks data mining
and the related architecture aspects and on privacy and
security issues.
The final goal of SOCRATE project is to exploit for
optimised radio network operation the knowledge
about the social structure of network users. Clearly,
this potentially exposes users to disclosure of sensitive
information. The disclosure of personal information, if
not anonymised, exposes also to additional threats such
as identity theft or even physical security or denial of
service or sabotage. Similar privacy and security ques-
tions are found in other applications, such as those
enabled by the Internet of Things (IoT) paradigm. In
this extension (Figure 3, top), we may use the term
user to mean a person or an entity possibly related to a
person, and the word social is used to refer to a person
or equivalently in more abstract terms to the contextual
relationship of devices.
IoT devices are increasingly permeating the human
environment. Connected sensors and/or actuators are
found for example in smart environments, cars and
wearables, in both industrial and nonindustrial scenari-
os. Whereas they serve a range of applications and
services, virtually any IoT device has access to sensing
data about humans or it acts on the environment hu-
mans live within and in particular on appliances and
services humans rely upon. Clearly, information securi-
ty, hence privacy, and physical security, hence safety,
are therefore unavoidable themes in such people-
centric IoT. More generally, security enforcement is a
fundamental enabler of the success of IoT and people-
centric IoT in particular.
IoT DEVICE IoT DEVICE
RADIO FEATURES, LOCATION, MOBILITY
IoT DEVICE
ATTRIBUTES
ATTRIBUTES
NETWORK
ATTRIBUTESATTRIBUTES
WIRELESS NETWORK
MANAGEMENTIoT SERVICE
CROSS-EXPLOITATION
IoT SERVICE
SOCIAL FEATURES
ATTRIBUTES
ATTACKERATTACKER
INT
I/F
EXT
I/F
ENH
AN
CEM
ENTSI/F
CONTEXT AND INFERENCE
ATTRIBUTES
WIR
ELES
S N
ETW
OR
KA
TTR
PEOPLE-CENTRIC SERVICE
OPTIONAL EXTERNAL SERVICE
DEPLOYED NETWORK
INTERFACES
Figure 3. A people-centric ICT scenario, above, and the conceptual framework supporting it, below. From Celen-tano et al. (manuscript).
BISG research in this area follows data minimisation
principles, where 1) occasions for collection of sensi-
tive data, 2) the extent of data collection, and 3) the
time duration of data storage are minimised. The
above, and the second point in particular, have direct
impact on architectural choices, see Figure 3.
At the top of the figure are depicted on the left the
people-centric IoT service and on the right the wireless
network supporting it. The objective is to infer obser-
vations of features at one domain and exploit them at
the other domain, through the enhancement protocols
shown in yellow at the bottom of Figure 3. By data
minimisation principles, attributes are stored at various
parts of the system to mitigate the threats of possible
attackers. Separated interfaces towards individual
sources guarantee flexibility of the design. Attackers
may target either side of the system (Figure 3, top).
Different scenarios enabled by the knowledge of social
structure and users’ features are compared in Höyhtyä
et al. (2016). Relationship among users and users’
preferences can be used to identify alternative data
distribution strategies, for example relying on clusters.
These strategies are then associated with corresponding
transmit power requirements. Options include changes
in the topology (direct data transfer from base station
BS to user equipment UE; or from BS to cluster-head
CH and then from CH to UEs; or having chunks of data
sent from BS to UEs, and then sharing them among
UEs). Considering the availability of various radio
access techniques (RAT), the above options can be
combined with changes in the RAT for communication
between CH and UEs and among UEs (LTE; WiFi).
The most power-efficient scheme depends also on the
INFOTECH OULU Annual Report 2016 4
required data rate, and in turn the data rate impacts on
transmission time and hence on energy efficiency.
Related to the above research and in the framework of
SOCRATE project co-operation, Celentano and
Röning are co-editors, together with collaborating
partners, of an IEEE Access special section on Recent
Advances in Socially-aware Mobile Networking.
Intelligent Systems Incorporating Machine Learning and Data Mining
Data mining methods for steel industry applications:
BISG is a member of the Centre for Advanced Steels
Research - CASR, which is one of the interdisciplinary
umbrella organizations of the University of Oulu. Year
2016 was the third year in participation to a large na-
tional research programme System Integrated Metals
Processing – SIMP.
One of the main goals in SIMP programme has been
the development of an innovative supervisor system to
assist the process development personnel and the oper-
ators of a steel production line over the whole produc-
tion chain, and to help discover new alternative solu-
tions for improving both the products and the manufac-
turing process. The quality monitoring tool (QMT) is
based on statistical models that predict different quality
properties and rejection risks in several process steps,
and it provides also model visualization (Figure 4). The
tool has been developed in co-operation with VTT, In
year 2016, QMT was delivered for online use at Ou-
tokumpu, Tornio and for offline use at SSAB, Raahe.
The development work continues, and the functionality
of the tool can be improved with the feedback of the
test period.
Figure 4. The tool for quality monitoring and visualiza-tion during the steel making process.
One of the models in QMT predicts the rougness of the
stainless steel surface with hot rolling parameters. In
previous case, the roughness was visually evaluated to
9 classes by experts in Germany. The goal was to pre-
dict the quality after hot rolling, before the product was
shipped to Germany for further processing. In 2016, a
new data was gathered with roughness measured with a
device. Although, the roughness type was in this case
different, the research revealed that also the finishing
step has a significant effect on the surface quality. The
new models will be implemented into QMT next year.
In the year 2016 one goal of the SIMP project was
reached, as the selection of combination parameters for
slab design were updated and improved with statistical
models. The aim of the combination is to ensure the
sufficiency of the material to produce the ordered
product with desired dimensions. The variance model-
ling increased the knowledge of process deviation and
the factors behind it. As a result, the new selection
procedure is expected to increase yield, reduce the risk
of rejection, energy consumption and emissions, which
in its turn improves the cost-effectiveness of the steel
mill. This study showed that using specific statistical
modelling methods and classification, the knowledge
behind the steel process can be pointed out and utilized
in manufacturing. Powerful data mining methods ena-
ble the effective use of process data in slab design. This
research is brought out vital problems in production
line and there has been a lot of development work done
also at SSAB, Raahe due to this study. The results of
this research were published in journal of Ironmaking
& Steelmaking on August 2016.
In the steel plate production process it is important to
minimize the wastage piece produced when cutting a
mother steel plate to the size ordered by a customer.
The uneven shapes at the plate end sides and lateral
sides cause yield loss, amounting to about 5% to 6% of
a total tonnage of slab used. To minimize the loss, aim
is to produce plates with concave side edges because
wastage from concave side edges is smaller than from
convex. We developed a method for automatic recogni-
tion of steel plate edge shape with classification and
regression models. First, we defined the curvature of a
time series describing the steel plate side edge, and
used this information to build statistical distribution
model to visualize what kind of curve shapes the stud-
ied data set includes and how the amount of curvature
is distributed in the manufacturing process. This infor-
mation can then be used to optimize manufacturing
parameters to manufacture more plates with desired
shape. Data for the study was collected from the steel
plate mill at SSAB, Raahe.
A tool for finding clusters of inclusions in SEM (Scan-
ning Electron Microscope) specimens of steel samples
was developed. The inclusion clusters may have a
significant effect on mechanical properties of the steel;
especially novel ultra-high strength steels require very
high steel purity. This tool enables quick and efficient
inspection of the specimens. The summaries of the
clusters are produced, as well as, visualizations of the
whole test area or interesting parts of it, The visual
presentation of the chemical composition of the clus-
ters helps to understand the birth mechanism of the
formation, and thus, to find a way to prevent it in steel
products. An example of a test sample from finished
product can be seen in Figure 5. One cluster has been
selected for a closer inspection, and it can be seen that
INFOTECH OULU Annual Report 2016 5
in this case there are only MnS particles in quite large
inclusion formation. The shape of the cluster is unusu-
al, but the direction of the test sample may explain it.
The research was carried out in the co-operation with
SSAB, Raahe.
Figure 5. An example of a clustered SEM specimen with zoomed in visualizations and the chemical compo-sition of the selected cluster,
SIMP programme will continue for another 6 months,
and we will present our research results annually on
SIMP and DIMECC seminars around Finland as well
as at international publishing venues.
Uncertainty of classification models. Many real-world
data sets contain missing data values. These might be
the result of e.g. malfunctioning sensors or some meas-
urements being too expensive to measure from every
sample etc. Having missing values when classifying a
sample means that there is an increase in uncertainty in
the final classification result. Knowing how uncertain
the result can sometimes be as important information
as the classification result itself. In an Infotech doctoral
program project, we are quantifying that uncertainty so
that interpreting the classification results becomes
easier.
Classification algorithms have traditionally been de-
veloped using complete data sets and most require
values for all variables to be present to work. Many
real world data sets are, however, cursed with missing
data. To tackle this problem, we developed an algo-
rithm that uses multiple imputation to handle the miss-
ing values. The algorithm can be used with any classi-
fier that supports estimation of class posterior probabil-
ities. The developed algorithm performs as well or
even better as a benchmark algorithm (see Figure 6)
and it does not require the classifier to support handling
of missing values.
The uncertainty does not, however, behave consistently
across different data sets. In a follow-up work we ad-
dressed this issue and the results of this work were
presented in a conference, see Figure 7.
Figure 6. Modelling the uncertainty as a function of classification rate.
Figure 7. Prediction of test sample uncertainty based on the uncertainty model from Figure 4.
INFOTECH OULU Annual Report 2016 6
Figure 8. Calibration plots from raw prediction scores, two commonly used calibration algorithms and our novel algorithm. Unpublished results.
To generalize these results, the classification confi-
dence algorithm was modified to a calibration algo-
rithm. In practice this means that the prediction scores
of a classification algorithm are attempted to get more
closely to resemble true posterior probabilities. Still
unpublished example of the performance this calibra-
tion algorithm compared to two state-of-the-art can be
seen in Figure 8.
Data mining methods for data of wearable sensors:
BISG has a long experience is studying data from
wearable sensors. Earlier the study has concentrated on
human activity recognition based on accelerometer data
from a wrist-worn device or mobile phone. This year
BISG extended the application area from human activi-
ty recognition to early diagnosis of diseases. In addi-
tion, we have used variety of sensors including elec-
tromyogram, thermometer, electrodermal activity sen-
sor and photoplethysmography sensor.
Human activity recognition: The activity recognition
approaches can be used for entertainment, to give peo-
ple information about their own behavior, and to moni-
tor and supervise people through their actions. Thus, it
is a natural consequence of that fact that the amount of
wearable sensors based studies has increased as well,
and new applications of activity recognition are being
invented in the process. In 2016 BISG concentrated on
studying human activity recognition in two scenarios:
adaptive models and comparing electromyogram data
to accelerometer data.
Usually human activity recognition is based on user-
independent models. However, as people are different
these models do not work equally well with every sub-
jects. Therefore, in order to obtain high recognition
rates with all users, models need to adapt to each user’s
personal movements. In our study, it was shown that
personal models can be trained without a separate data
gathering session if wearable device has several types
of sensors. On the other hand, it was shown that per-
sonal models always do not provide as high recognition
accuracies as reported in the literature. The reason for
this is that models are not general enough and therefore
they cannot react to changing conditions. In fact, in
order to build reliable user-dependent recognition
model, a lot of personal data needs to be collected. This
requires an extensive, separate data collection session
for each user. If the aim is to build a commercial appli-
cation for the masses, this is far from ideal situation.
However, BISG introduced an noise injection based
method to expand the area covered by training data,
and in this way, make the models trained using it more
general and less vulnerable to changing conditions.
This is shown to improve the recognition rates, espe-
cially if the amount of the training data is small. An
another approach to tackle the same problem a solution
combining the human independent and personal mod-
els more effectively using self-organizing maps based
distance as a selection criteria was introduced. By us-
ing the approach, the selection can be done in real time
and within wearable device itself. The results show that
the approach clearly outperforms posterior probability
based approach in preserving the high recognition
accuracy regardless of which model is used.
BISG also studied the possibility to use electromyo-
gram data to recognize human activities. The actual
research problem tackled is one of the major drawbacks
in activity recognition, namely to add completely new
activities in real life to the recognition models. In this
study, it was shown that in gym settings electromyo-
gram signals clearly outperforms the accelerometer
data in recognition of completely new sets of gym
movements from streaming data even though the sen-
sors would not be positioned directly to the muscles
trained. However, it was noted than when the task is to
recognize previously known activities, accelerometer
data outperforms electromyogram signals.
Early diagnosis: The progress in the sensor develop-
ment including improved memory and battery proper-
ties has made possible to measure human physiology
24/7, and more importantly with such accurate readings
that have previously been possible only in laboratory
settings. BISG is aiming to use a single, easy and com-
fortable device to measure 24/7 data from persons bio-
signals and based on these recognize upcoming sei-
zures. For this purpose BISG got a six month funding
from TEKES from Challenge Finland program.
Though the funding period was short, promising results
were obtained. The first use case was based on mi-
graine. The migraine is a chronic, incapacitating neu-
rovascular disorder, characterized by attacks of severe
headache and autonomic nervous system dysfunction.
Moreover, migraine headache is usually associated
with nausea, vomiting, or sensitivity to light, sound, or
movement and when untreated, typically lasts 4 to 72
hours. Typical migraine attack consist of five phases:
prodrome (e.g., food craving), aura (e.g., visual, senso-
INFOTECH OULU Annual Report 2016 7
ry, or motorsymptoms preceding the headache), head-
ache (usually unilateral, pulsating), resolution (pain
wanes), and recovery. The illustration of these phases
are shown as Figure 9. The migraine condition starts in
over 40% of the cases before 18 years of age, thus
making it also a childhood disease. The medication of
migraine can be divided into two categories: preventive
(daily dose) and acute medication (when symptoms
start). The preventive medication is an expensive solu-
tion and especially with children, it is avoided as long
as possible. On the other hand, the problem with acute
medication is that some people do not have early symp-
toms, some tend to easily dismiss the early symptoms,
sometimes even on purpose. Thus the early diagnosis
of migraine attack would be a valuable addition to
treatment of the disease. The research concept was
aimed to early detection of migraine attach based on
human bio-signals collected with wearable sensors is
presented. In our approach, the idea is to use a single,
easy and comfortable device to measure 24/7 data.
Results from this project will be published in 2017.
Moreover, BISG is actively seeking new funding pos-
sibilities and instruments to continue in studying the
early diagnosis also in 2017.
Figure 9. Phases of typical migraine attack.
Developing software for data mining in public health:
The multidisciplinary MOPO project combined tradi-
tional health promotion, modern technology and meas-
urement of physical activity. Altogether about 6000
conscription aged men (five call-up age classes) were
invited to participate in the study, where the partici-
pants’ physical condition, well-being, health, relation-
ship towards physical activity, information behaviour
and use of media and technology were investigated
during the years 2009–2014 using questionnaires,
measurements and interviews. In addition to this, a
novel wellness coaching service for preventing mar-
ginalization and promoting physical activity and health
in young men was developed in the project. The ser-
vice, which took the form of a gamified Web portal
optimized for mobile devices (Figure 10), was devel-
oped by BISG personnel and incorporated functionality
for collecting, storing and analysing physical activity
data and presenting the results of the analysis to the
user as personalized feedback.
The Web portal went through a number of iterations
that were evaluated in a series of intervention studies,
culminating in an intervention where access to the
portal and a wrist-worn activity monitor was given to
approximately 250 conscription-aged men (Figure 11).
The intervention started in autumn 2013 and lasted 6
months. Following this final intervention, the lessons
learned over the course of the MOPO study were gen-
eralised into a set of design principles intended to be
applied by medical researchers and software developers
implementing digital interventions for health behaviour
change. A paper on the proposed design principles was
published in 2016. Also in 2016, BISG researchers
contributed to an analysis of MOPO data comparing
self-reported versus measured physical activity and
sedentary behaviour.
The operators of the MOPO study were the Oulu Dea-
coness Institute’s Department of Sports and Exercise
Medicine, the University of Oulu, the City of Oulu, the
Virpiniemi Sports Institute, the Finnish Defence Forces
and several wellness technology companies in North-
ern Finland. The project website can be found at
www.tuunaamopo.fi.
Figure 10. The Web portal offers tailored information
about topics such as physical activity, fitness, health,
and nutrition.
INFOTECH OULU Annual Report 2016 8
Figure 11. In autumn 2013, 250 conscription aged men were recruited from call-ups to test the wellness coach-ing service developed in the MOPO project.
Foundations of knowledge discovery and data mining:
Knowledge discovery in data (KDD) was defined in
1996 by Fayyad et al. as “the nontrivial process of
identifying valid, novel, potentially useful, and ulti-
mately understandable patterns in data”. Although this
definition still has its merits, it represents a rather nar-
row interpretation of the concept of knowledge that
may prove a hindrance to the development of more
advanced KDD tools. Meanwhile, the seminal process
model proposed by Fayyad et al., which depicts the
KDD process as a sequence of five major steps, is still
embedded in most KDD process models, including the
standard model CRISP-DM. This established model,
while essentially correct, represents a limited perspec-
tive on the KDD process that is likely to prove inade-
quate in the long run.
In its research on the foundations of KDD and data
mining, BISG has sought to expand this traditional
view of the nature of KDD. The resulting model, like
the established one, accounts for the data transfor-
mations required in order to get from raw data to
knowledge, but also for the actors of the process and
the interactions among them that need to take place for
the process to move forward. Furthermore, the model
explicitly considers the contributions of non-expert
actors, as well as the possibility of technology taking
on a more autonomous role in the process, which is
likely to be realized in the near future as KDD software
grows more intelligent and becomes capable of han-
dling tasks that currently require a human actor. Hav-
ing a model that provides a more complete account of
the KDD process is essential in unlocking the full po-
tential of KDD technology, which in turn is crucial in
making sense of the deluge of digital data that seems to
have become a permanent feature of high-technology
societies. Figure 12 illustrates the process actors and
how different interactions among them lead to different
types of KDD processes.
Intelligent Systems Incorporating Robot-ics and Cybernetics
euRathlon Summer School
The ERL Emergency/TRADR summer school 2016
was organized from the 22nd to 26th of August by the
robotics group members and the staff from TRADR
(Long-Term Human-Robot Teaming for Disaster Re-
sponse). The summer school was attended by 55 stu-
dents, mostly doctoral, originating from 17 different
countries (Figure 13). Also, 6 invited lecturers from
TRADR held lectures during the summer school. Ac-
cording to the satisfaction survey, the participants were
very pleased with the summer school as all of those
who answered the survey would recommend it to oth-
ers.
Figure 12. The actors of the KDD process can be illustrated as the vertices of a triangle, with technology in the cen-ter, being both an actor in its own right and a mediator of interactions among human actors (a). The process can take on a number of different forms, characterized by which of the actors are present and how they interact: the standard KDD process (b), KDD using personal data (c), KDD using volunteer computing (d), and KDD driven by a non-expert actor (e). A good example of the latter is the so-called Quantified Self movement.
INFOTECH OULU Annual Report 2016 9
Figure 13. Attendees and organizers in the ERL Emer-gency/TRADR summer school 2016 held at the Univer-sity of Oulu.
This year, the ERL Emergency summer school focused
on developing algorithm for controlling land robots
with a strong focus on SLAM and multi-source persis-
tent data integration.
In total, the summer school lasted for four and a half
days consisting roughly 35% of lectures and 65% of
practical exercises in which the students developed
control and SLAM algorithms. These practical sessions
were held indoors in the University of Oulu’s facilities
and outdoors in a nearby (less than 1km of walking)
botanical garden where electricity, shelter and internet
access were also provided. The hands-on practices
culminated to a challenge scenario that each team per-
formed on the last day at the botanical garden.
The students were provided with two of TRADR’s
UGVs and one UAV (Figure 14) provided by Ascend-
ing Technologies. The students could modify and de-
velop software for the two UGVs but the UAV was
flown only by the trained representative of Ascending
Technologies. Before the summer school, these UGVs
and UAV were also used to gather preliminary data for
software development during the exercises. The raw
data was used to form initial maps that were given to
the students to work on for testing and performing
simulations. This was done to reserve the students’
time for more meaningful tasks as the generation of
maps from raw data takes many hours of processing on
a desktop computer.
During the registration process the students were asked
to provide a brief description of their programming
experience. This info was used on the first day to form
eight balanced teams of six or seven persons. The bal-
ancing was done mainly in regard of C, Python and
ROS experience as at least one person in each group
had to have at least basic understanding of these to
ensure that the practices would proceed in a timely
fashion.
Figure 14. TOP; One of the two identical unmanned ground robots (UGV) provided by TRADR. BOTTOM; The UAV, AscTec Falcon 8, provided by TRADR part-ner Ascending Technologies.
On the first day the student teams were presented with
a challenge scenario they would perform and compete
on the fifth, and last, day of the summer school. The
scenario consisted of a simulated toxin leak at the bo-
tanical garden and the teams’ task would be to find and
localize the toxic materials using the UGV, UAV and
the pre-recorded maps of the area.
To fulfil this task, the teams needed to fulfil the sub-
tasks:
Map the area using one UGV and one UAV.
Update and refine the map based on new data.
Develop strategies to safely navigate the UGVs in
the danger zone.
Navigate the UGV to designated points of interest
with the highest degree of autonomy possible.
Detect objects automatically if possible.
Have the UGV perform automatic collision avoid-
ance if possible.
The practical sessions focused on developing ways to
fulfil these tasks and mapping the scenario area (see
Figures 15-18).
INFOTECH OULU Annual Report 2016 10
Figure 15. The used waypoint planner and simulator.
Figure 16. Outdoor testing at the botanical garden.
The challenge scenario was run on the final day of the
summer school. The toxic leaks were simulated with
bright balloons and rough estimates of their locations
were given to the teams. Compared to previous days,
the scenario environment was somewhat changed by
added obstacles (chairs, tables, etc.). Each team had 30
minutes of time to complete the mission, during which
they had full access to the UGV. The teams also had a
limited 5 minutes access to the UAV, flown by the
trained operator, to get a rough overview of the envi-
ronment.
Figure 17. Scenario briefing and composed map of the area.
The students were also given a demonstration of the
Aquamarine Robots Dolphin marine robot.
Figure 18. Aquamarine Robots Dolphin robot shown during the summer school.
INFOTECH OULU Annual Report 2016 11
Robotics Research
In 2016 BISG had a wide range of research in the area
robotics, including industrial safety, aerial data gather-
ing, battery life management and control of complex
wheeled land robots.
ReBorn
The EU funded ReBorn project has ended. The project
had participants from 17 industrial and academic insti-
tutions from 10 different countries. During the project,
the sufficiency of current standards related to robot
development and reusability in industrial environments
was investigated by a paper review and by surveys sent
to the project partners. The current standards (Figure
19) for designing user safe robots were deemed suffi-
cient for fulfilling the requirements to implement safe
robots for traditional industrial applications. However,
in some applications shortcomings in the currently
available standards were found.
Figure 19. Main standards applicable in implementing user safety in industrial robotics.
One of the commonly mentioned issues was that there
is a lack of standardized commonly applicable perfor-
mance descriptions for the existing line of robots. This
especially hinders the flexible use of heterogeneous
and modular robotics. Also, reuse and repurposing old
robots for new applications is more difficult without a
common form of performance descriptions and capa-
bilities of the robots. It was also found out there cur-
rently are no dedicated ISO/EN/DIN standards specifi-
cally related to safety and design assisting in imple-
mentation of reconfigurable manufacturing cells. Other
area that was mentioned in the survey responses from
the project partners was the lack of LCC (Life Cycle
Cost) standards, similar to what are already in use in
the building construction industry.
One area of interest in the project was the requirements
for implementing CWS (Collaborative Work Spaces).
In this field, some standards already exists (Figure 20)
that can be utilized to implement the minimum safety
features required to avoid serious injuries. However,
from the applications side, the standards are currently
vague on how the software should be implemented and
how the user should be taken in to account as an agent
acting in the control loop when performing tasks co-
operatively with a robot. The actions of the human in
the loop needs quite a lot of prediction and behavior
observation to implement co-operation efficiently and
safely in flexible manufacturing units. This is an area
that is currently under a lot of research and appropriate
standards should also be developed on how the user
monitoring and behavior prediction should be per-
formed on hardware and algorithm level.
Cloud computing is an area that could be better utilized
in industrial environments as a channel for data pro-
cessing, learning and teaching of industrial robots in
the future. Cloud computing could also be used for
openly collecting and sharing data about robot reliabil-
ity for evaluation of the reusability, safety and costs of
running specific types of robots in certain tasks.
Figure 20. Standards applicable for collaborative work spaces.
NORDUM Exercise
NORDUM (Intercomparison of Nordic unmanned
aerial monitoring platforms) exercise was organized in
the Hauerseter Leir military campsite, Gardermoen,
Norway. The NKS-B activity NORDUM is the first
joint Nordic exercise for unmanned systems. All in all,
five teams participated in this event coming from dif-
ferent universities and radiation safety related institu-
tions located in Norway, Sweden and Finland.
In the NORDUM exercise, the objective was to locate
and identify potential radioactive materials from the
arranged scenario areas. The scenario areas varied from
cluttered areas containing large shipping containers and
various metal structures to open field and forest scenar-
ios. For the measurements, a stand-alone sensor pack-
age was constructed containing a RTK (Real Time
Kinematic) capable GPS (u-blox C94-M8P-3), meas-
urement computer (Raspberry Pi 3 Model B), a 433
MHz (3DR) radio, a 3.7V Li-ion battery and a gamma
radiation spectrometer (Kromek GR1-A).
In the arranged scenarios, the teams needed to localize
hidden radiation sources and visualize their location
utilizing GPS. In the scenarios, the constructed stand-
alone sensor package performed well in most scenari-
os, although some radio link related issues were en-
INFOTECH OULU Annual Report 2016 12
countered especially near large metal structures. The
utilized Kromek GR1-A was sensitive enough that
radiation sources could also be identified from local
spectrum histograms when enough flybys near the
radiation source was made.
The stand-alone sensor package was carried with a DJI
Inspire 1 T600 quadcopter, hanging 1.5 meters below
the vehicle. This made possible manoeuvring the sen-
sor very close to the objects being measured. The
quadcopter had a flight time of 10 minutes with a 5.7
Ah 22.2V Li-ion flight battery and the sensor package.
The 4k resolution camera was utilized during flight to
observe the sensor position and to manoeuver it to
wanted positions. Although the conditions were rather
windy, flying with the sensor package was manageable.
The quadcopter with the sensor package is shown in
Figure 21. The measurement results from one of the
three scenarios is shown in Figure 22 and Figure 23.
Figure 21. The DJI Inspire 1 carrying the constructed stand-alone sensor package containing a GPS, a radio transceiver and a gamma radiation detector. On the right is a still image captured by the onboard 4k resolu-tion camera.
Figure 22. Gamma radiation measurements made with the stand-alone sensor package carried by the quad-copter in one of the testing scenarios. The brightness of the green color indicates the intensity of the detected gamma radiation activity.
Figure 23. Local histogram collected from area en-closed by the red circle 3 in the scenario image. The detected spike corresponds with Cs-137 (Cesium with a theoretical gamma radiation energy emissions of 661.64 keV).
Robots
The Mörri robot has been equipped with more easily
maintainable and more powerful electronics in its rein-
carnation. The main drive electronics are now mostly
off-the-shelf components controlled with an Ardupilot
APM2 based controller that is connected to an onboard
computer handling the overall robot control and com-
munications with a remote control station. The Mörri
platform is also used in testing the test batch of intelli-
gent battery modules that have been constructed. The
functional diagram of the new drive system is shown in
Figure 24 and the Mörri mobile platform in Figure 25.
Figure 24. The overview of the renewed fundamental electrical system required to drive the Mörri robot.
Figure 25. Mörri with Microsoft’s Kinect 2 sensor driving on a field and on snow with tracks put on.
In anticipation of performing joint missions simultane-
ously with multiple UAVs and UGVs, also custom
quadcopter platforms are being constructed. The basic
platform, shown below in Figure 26, is low-cost and is
constructed from off-the-shelf components for better
maintainability. The quadcopter platform is built
around the open-source ArduPilot PX4 flight control-
ler, allowing more freedom for customization and test-
ing our own implementations required for autonomous
operation, which is not as easy to do with most prebuilt
and significantly more expensive quadrotors. Com-
bined with LIDAR (Light Detection And Ranging), the
copters will be used for SLAM and environment classi-
fication efforts in joint missions with UGVs, such as
Mörri. Because both Mörri and the quadcopter utilize
ArduPilot based controllers, the development of both
platforms is simpler due to having very similar proto-
cols for using the controller responsible for inertial
measurements and platform control.
INFOTECH OULU Annual Report 2016 13
Figure 26. A semi-ready customizable low-cost quad-copter platform.
Intelligent battery modules
Intelligent battery modules (Figure 27) have been de-
veloped in collaboration with Probot Ltd. and the test
batch is being tested with our robot platforms. The
initial tests of the test batch have showed that the de-
signed battery electronics are functioning as was in-
tended. The battery module has an integrated heater for
winter operation and a charger module allowing energy
transfer from one module to another in any parallel
connected energy bus. With a developed charge control
module, the bus can also be potentially used to recover
energy from multiple power sources, such as solar
panels.
Figure 27. Assembled intelligent battery module for general use in modular robotics.
Control of Complex Wheeled Robots
Pseudo-omnidirectional robots with individually steer-
able wheels offer a good balance between payload,
robustness and mobility. However, the non-holonomic
nature of the regular wheels and the often redundantly
actuated structure of these robots make their control a
complex issue. This complexity of control is further
exacerbated when the wheels are not rigidly connected
to the robot body but are instead connected via actuated
chains which allow the wheels move relative to the
body. BISG has developed control algorithms for such
Articulated Wheeled Vehicles (AMW). The control
algorithms are mathematically simple closed-form
analytical functions and are thus computationally light
but are currently limited to planar cases. The computa-
tional load is only linearly dependant on the number of
wheels making the developed control algorithm suita-
ble for multi-wheel configurations and/or low-powered
embedded MCUs. The control algorithms synchronize
the rolling and steering velocities of complex planar
robots (plausible simulated example in Figure 28) with
freely located wheels forming fixed or variable foot-
prints. The rolling and steering velocities remain syn-
chronized even with very complex motions of the robot
(Figure 29). With the developed control algorithms, the
traversable path, robot’s heading on different points of
the path and the path velocity can be controlled sepa-
rately, thus offering great freedom on how to control
the robot on a given practical task. The control algo-
rithms do not in practice suffer from representation
singularities which are a common problem in wheeled
control. The control algorithms also compensate for the
proximity of mechanical singularities by adjusting the
robot’s path velocity according to the maximum capa-
bilities of its wheels’ steering and rolling actuators. In
fact the developed control algorithms are time optimal
in a sense that at any given moment the robot is either
traversing with maximum allowed path velocity or at
least one of its steering or rolling actuators is turning at
its maximum velocity (Figure 30), i.e. the robot
traverses the given path in the given way with the giv-
en velocity restrictions as fast as it possibly can.
Figure 28. Example of complex wheeled planar robot.
Figure 29. Simulation run of Figure 26’s robot traversing a given yellow path while keeping its front directed at all times to a point of interest (green larger dot). Note the smooth convergence of the robot (black line) and the target path.
INFOTECH OULU Annual Report 2016 14
Figure 30. (Top) wheel rolling speeds, (Middle) wheel
steering speeds and (Bottom) robot path velocity for
the first 30 seconds of a simulation run.
In summary, the developed control algorithms can be
used in a wide range of robot configurations and sce-
narios with low computational cost. The control algo-
rithms are currently limited to planar surfaces and can
cause sudden and large changes in velocity and the
control algorithms are being extended to work also
with uneven surfaces and limited motor torques.
In year 2016 the control algorithms have been en-
hanced to allow the wheels to have non-zero lateral and
longitudinal offsets, making the algorithm suitable for
practically any configuration of a wheeled planar robot.
In addition, a path tracking algorithm was developed.
The algorithm is very simple yet provides smooth and
robust path convergence in simulated environments
(Figure 31).
Figure 31. Smooth path convergence in cluttered envi-ronment.
Two ERDF project started; Labrobot and OuluZone+
projects. Labrobot focuses on Food industry, and
OuluZone+ for autonomous vehicles in harsh condi-
tions.
Labrobot-project focuses on boosting regional Food
industry by technology transfer demonstrations, build-
ing up test facility and network of stakeholders. By
surveying challenges in factories, combined with
knowledge of robotics, big data, machine vision and
biotechnologies; new kind of solutions are searched for
base of new business possibilities. This project is done
in cooperation with Center of Machine Vision and
signal processing, Biocenter Oulu and Luke. Project is
partly funded by City of Oulu, Yaskawa, Probot,
Maustaja, Antel, Kinnusen mylly, mekitech, and SR-
Intruments.
In the OuluZone+ project the focus is on automatic
road building machines and smaller mobile robots
(UGV and UAV) for supporting operation on the field.
In the project are studied how the capabilities of auton-
omous cars could be formally verfied, and tested from
perspectives of operting in all weather conditions and
all situations. Project is partly funded by City of Oulu,
OSEKK, Ouluzone Operointi Oy and industrial part-
ners.
The Evolutionary Active Materials
The Evolutionary Active Materials (EAM) project,
which is funded by the Academy of Finland, is a joint
effort between the Computer Science and Engineering
laboratory (CSE) and the Microelectronics and Materi-
als Physics laboratories. The aim of the EAM project is
to develop novel, evolutionary computation (EC) based
design methods for active and versatile materials and
structures. The first components are being developed
through a novel holistic design process utilizing con-
stantly increasing computation power, the development
of multi-physics simulators, and EC techniques, such
as genetic algorithms (GA).
During 2016, the height and the top diameter of Cym-
bal type piezoelectric actuator were optimized by ge-
INFOTECH OULU Annual Report 2016 15
netic algorithm and FEM modelling. From the opti-
mized results, maps of electromechanical capabilities
of different structures were generated. The blocking
force of the actuator was maximized for different val-
ues of displacement by optimizing the height of the cap
and the length flat region of the end cap profile. By
using values obtained from a genetic algorithm optimi-
zation process, a function was formulated for design
parameters. Using the function, a map of displacement,
the steel thickness and the height of the end cap the
optimized length of flat region was constructed (Figure
32). A similar map with the length of the flat region for
the optimized height of end cap was created. The re-
sults will be published at 2017.
Figure 32. The top diameter of the steel cap as a func-tion of steel thickness and displacement for Cymbal.
New type of actuator called Mikbal (Figure 33) was
invented, optimized with genetic algorithm and
realized. Mikbal was developed from Cymbal by
adding additional steel structures around the steel cap
to increase displacement and save the amount of used
piezoelectric material. The best displacement to
amount of used piezo material ratio was achieved with
25 mm piezo material diameter in the case of 40 mm
steel structures, and lower height and top diameter of
the cap increased the displacement. The results will be
published during 2017.
Figure 33. The von Mises stresses in Mikbal actuator under 500 V voltage.
Also optimization of the end cap structure of the Cym-
bal type energy harvester was done with genetic algo-
rithm and FEM modeling software Comsol Multiphys-
ics. The aim was to improve harvested power levels
from human walking (Figure 34). The power produced
by the energy harvester was increased by allowing the
algorithm to modify thickness in certain regions as
grooves in the end cap. By evolution of the structure,
power produced by the harvester increased by 38 %
compared to traditional linear type Cymbal harvester
which was also optimized by the algorithm. Increase in
power was obtained by change of mode in mechanics
of the harvester by grooves.
Figure 34. Cymbal type energy harvester in a shoe and an optimised profile for the harvester. In the profile piezoceramic disc is depicted in yellow and steel cap in grey. The grooves shown in the left side of the profile have been found by the genetic algorithm.
New grooved Cymbal energy harvester (Figure 35)
gave promising results in physical measurements pro-
ducing same power with less force than uniform shape.
The model was invented based on results given by
genetic algorithm optimization process with spline
shapes. Grooved Cymbal is easy to produce compared
to spline shape. Depth and place of grooves were opti-
mized by genetic algorithm. The parameters of the
algorithm itself were optimized also with GA, called
metaGA. Results of the metaGA will be published
during 2017.
Figure 35. Grooved cymbals.
INFOTECH OULU Annual Report 2016 16
Intelligent Systems Incorporating Bio-IT solutions
We have taken part in the Ruby/Diamond HILLA pro-
ject. This was based on collaboration between the poly-
techniques, VTT and BISG. This and a previous Tekes
project lead to establishment of four strategies that
should offer openings in the aims to establish minimal-
ly invasive of non-invasive wellness and health param-
eter monitoring technologies. Via a collaborative net-
work, we acquired novel nanomaterials offering ways
to couple electronics to biomonitoring behaviour of
live cells.
Developing novel real-time biosensors for glucose
monitoring. For developing “second generation biosen-
sors”, we have taken use of our skills to purify and
culture the skin derived progenitor cells that are re-
sponsible in skin renewal and regeneration. We ob-
tained for the project a Tekes strategic opening fund-
ing. With this support, we have advanced the work to
develop of a novel biosensor strategy (Figure 36).
Figure 36. Novel biosensor strategy. Donor skin renew-
ing cells are set to culture and a specific responsive component is engineered to target a tag to the 3´end of the coding sequence in the genome. Such a cell is then implanted to the donor to serve as a measure for a given physiological parameter. These serve to offer novel ways to biomonitor in real time physiologically relevant factors with and external electronic reader that is coupled wirelessly to the cloud to data analysis of multiple sensors at the end.
By now, we have been able to conduct the proof of
principle set up in the sensor construction. These indi-
cate that the skin is indeed responsive to the changes in
certain serum constituents. The data also indicated that
the cells with in the skin can also be engineered and be
converted genetically to serve as biosensors, thus to
report changes in the physiological parameters such as
glucose. We have screened in selected biological phe-
nomena with the proteomics and transcriptomics the
respective mediators in the glucose response in the
skin. We also generated experimental diabetic models
to identity diabetes associated and insulin independent
responders. The approach has turned a successful one.
First of all the skin appears responsive for physiologi-
cal levels of glucose. Due to this reason we also were
able to identify candidate factors whose genes and
encoded are currently being engineered to convert the
respective protein into an isoform whose activity can
read with an external electronic device.
We have also tested the capacity to culture of FACS
purified cells of the skin and if such cells can be trans-
planted with a fluorescent tagged vital sensor cells to
the donor so that the cells indeed become incorporated.
We assayed the stability of the sensor cells as trans-
plants. The data suggest that a syngeneic host suggest-
ing that the aimed biosensor strategy is feasible accepts
the skin progenitor graft.
In collaboration with VTT we have also developed the
electronic unit, a tunable spectral camera. This has the
capacity to measure the changes in the skin basal pro-
genitor cell integrated sensor. We have filed a patent of
these biotechnological avenues with VTT.
Developing an ex vivo supernatural personal mobile
biosensor device. To advance the goal to develop novel
wearable sensory devises we started to assemble first
via a HILLA funded project a micro fluidistic set up
that will be converted to a bio recognition tool. During
the research period, several micro fluidistic prints were
planned, made and tested. Out of these a configuration
was obtained that collected successfully, the skin asso-
ciated fluids as depicted by the presence of color dye in
the fluidistic chamber (Figure 37). A patent search of
the strategy has been conducted.
Figure 37. A micro filudistic print design is able to col-
lect the skin-associated fluids as depicted by the accu-mulation of a blue indicator dye in the chamber.
During 2016, we developed capacity to the micro fluid-
istic set up to monitor specific biomolecules present in
the skin fluids. This work lead to an opening via identi-
fication of novel types of biological nanomaterial’s
from the skin. These components are generated nor-
mally by the cells, they cargo wealth of physiologically
relevant biomolecules and they can cross the biological
barriers. Given the numerous amounts, small size of
the nano scale components, the opening has stimulated
a need to establish both bio and databanks. This is
INFOTECH OULU Annual Report 2016 17
currently being conducted with via deep sequencing
and proteomics to diagnose the samples that are de-
rived from cohorts.
During 2016, wealth of medical technical developmen-
tal lines with VTT and companies have been initiated
and also a new Tekes project grant filed. We obtained a
new Academy of Finland funded grant from the Bio
Future 2025 program to advance the nanobioelectronic
analysis strategies, one of the Infotech Oulu research
program targets.
To advance the biosensor openings we have started to
develop at the same time more complex diagnostic
platforms as the fluidic champers. To be able to read
the fluorescence that is revealed by specific antibodies
bound to the diagnostic components reagents against
these factors are being developed during 2017 with our
collaborator. Our partners in the HILLA project were
able to develop a mobile phone based micro fluidistic
reader capacity. Together with the developed biochips,
such printable materials are likely to set the stage for
the point of care diagnostics in the field of personalized
medicine during 2017.
Screening of electromagnetic and opto/chemo/electro
genetic responses in organs generated from stem cells. The genetic engineering offers opportunities to devel-
oped technologies where the cellular in or output sig-
nals can also be regulated by certain wavelengths in the
electromagnetic spectrum. Alternatively the cellular
actions can be genetically constructed so that a signal
will be transmitted to a biosensor that will convert it to
a form readable by an electric device. To advance these
tasks we have initiated with private funding screens
that aim to identify cellular channels that are regulated
by specific spectral frequencies such as the RF ones.
Such diagnostics use a paradigm shift where the cellu-
lar responses to given stimuli will be screened primari-
ly via vital “biosensors” with live cellular tags. Thus
the approach in the bioelectronics analytics have be-
come possible via the crisp Cas9 genome-editing tech-
nologies where libraries of gene edited diagnostic cells
can be generated.
During 2016, we developed novel tissue engineering
technologies that do enable introduction of specific
gene expression constructs to individual cells of the
model organ such as the mammalian kidney. Here the
organ primordia is dissociated to single cells, the genet-
ic construct encoding the protein of interest such as the
opto, chemo or radiogenetic responsive component is
transduced to such a cell with a reporter for the read
out screens. There after the organ is let to self-assemble
and placed for a long-term culture (Figure 38).
Figure. 38. An organ primordia can be dissociated to single cells, the constitute cells transduced with a ge-netic construct to acquire opto-, chemo- and radio ge-netic guidance capacity to the morphogenetic cells ex vivo.
With the developed model systems we have taken use
of the image analysis technologies to visualize how the
morphogenetically active cells behave in three dimen-
sion in the 4D conditions that offer a whole organ pri-
mordia to be cultured ex vivo. To achieve this we
applied defined pressure to the assembled organ pri-
mordia in ex vivo setting depicted in Figure 39.
Figure 39. The 3D kidney organ primordia that is rela-tively thick being composed of multiple cell layers de-velops also under a mild pressurize in ex vivo. Here the mechanical pressure converts the 3D development more towards a 2D configuration. The developed setup will offer ways to identify pressure sensors in the cells and also to develop novel organ pressure monitoring tools. The power of this novel “organoid” culture set up is that it enables for the first time is complex organs image analysis and follow up of the behavior of the individual constituent cell while the complex 3D anatom-ical structure of the organ become laid down. It is im-portant that the quality of the data good enough to offer segmentation and “computer vision” analysis. With such “Fixed Z-Dimension” (FZD) culture we are in a process of illustrating the fine details how biological shapes, namely the organ structure in 3D becomes constructed from the cellular building blocks. These data serves also as the digital 3D landscape for developing 3D bio printing when advancing a European Union FET
INFOTECH OULU Annual Report 2016 18
FLAGSHIP representing a regenerative medicine and nanotechnology initiative.
We found that under a defined pressure the organ flat-
tens towards two dimension (2D) but yet morphogene-
sis progressed (Figure 40). This novel set up has made
it possible follow the fate of individual cells is the cells
are constricting a detailed manner while the natural
form.
Figure 40. Operetta confocal workstation coupled to a robotic set up and an incubator was assembled. A) A
holder for plates and transported by the robotic arm (B) and the cells with in will be transported to an incubator (C). The whole set up is inside a hood (D) and the ro-botic arm transports the plates to the Operetta confocal semi-high throughout microscope fluorescent reader. The data is analyzed by wealth of machine vision/image analysis programs present with in the assembled bio robotic set up. The bio robotic core facility will be used to screen with a library of live indicators cellular re-sponse to specific frequencies in the electromagnetic spectra.
To target the detailed dynamics by which the form is
assembled in a model organ we took use of the genet-
ically engineered Wnt4CreGFP knock in mouse model.
This was crossed to the floxed Rosa26 Yellow Fluores-
cent Protein (YFP) transgenic mice. In this genetic
crossing the stem cells that generate whole of the neph-
ron will become labeled with the YFP.
With the fixed Z-dimension culture we have captured
3D movies from the developing kidney with the confo-
cal microscope in a time-lapse setting. We are in a
process of analyzing the detailed cell behavior via the
machine learning/computer based image analysis with
Prof. Janne Heikkilä. With Dr. Jari Juuti we aim to
construct a specific device that allows detailed measure
of the pressure forced encountered by the tissue under-
going morphogenesis. These novel capabilities now
allow analysis in great detail the mode by which the
spatial and temporal organization of the cells go on to
construct natural form that is open at present in any
developing organ system. We will use models to identi-
fy the pressure sensors from the cells with the OMICS
technologies.
Developing high throughput robotic aided platforms to
screen complex cellular responses to magnetic/electric
fields via signaling pathway reporters. To advance the
strategies to measure in a high through put manner the
cellular responses to stimuli we have assembled a bio
robotic workstation. Here an Operetta confocal micro-
scope was obtained and this was coupled to a hood that
contains an automated plate-cargo arm, a rack for the
plates with a bar code reader and incubator for long
term exposure of the cells to compounds such as drugs
or specific electromagnetic spectral radiation (Figure
40). The Operetta confocal microscope has machine
learning/image analysis capacity for wealth of meas-
urements to be conducted from the cells.
To take use of the set up a yeast cell library was ob-
tained and three replica clones from it was generated
and stored for later use. The library is composed of cell
where each of the 3´end of each of the yeast gene was
targeted by a green fluorescent protein (GFP) tag. The
next goal is to obtain capacity to start to use the set up
to define the oscillating properties of the cellular genes
and to use it as live measures for screening responses
to stimuli such as those mediated by the opsins for the
visible light frequencies. Such genome wide screens
vital bio indicator based scan be expected to lead to
identification of novel biosensor pathways for certain
spectral frequencies. When the strategy will be subject-
ed to patient derived gene edited human induced plu-
ripotent (iPS) cells and those whose fate has been engi-
neered to defined directions this technology should
offer avenues for the era personalized medicine diag-
nostic developmental aims.
Intelligent Systems with cohort data sets: Cohort data
set is a special data set from the medical domain, which
has not been studied with a machine learning approach
before. The data set, Northern Finland Birth Cohort
1966 (NFBC 1966), is a unique data set with over 14
000 original variables in various yet heterogeneous
formats (numerical, ordinal, categorical, images, text
etc.) from a population of over 12 000 mothers and
their children without any complete data points. The
amount of variables rises to millions if genetics and
epigenetics are considered (p >> n).
There are two extremely important aspects of modeling
this type of data: confidence of the predictions made
with the model and model interpretability. Steps to-
wards instance level confidence estimates have been
made in our previous work (see above) and we will
continue to pursue this goal, along with keeping model
interpretability in focus also, when we start digging
into this fascinating data set. Our goal is to use a ma-
chine learning approach to make novel discoveries
from the data that traditional data analysis approach
has not yet uncovered.
Elders are an increasingly large fraction of the popula-
tion in developed countries. From one hand people
INFOTECH OULU Annual Report 2016 19
expect an independent life also in presence of more or
less important diseases. On the other hand the treat-
ments to care those diseases, often together with co-
morbidities, imply larger costs. To respond to both
these goals, the disease progress should be kept as low
as possible (see Figure 41), which means early disease
detection, deinstitutionalisation and personalised medi-
cine, striving to allow a better quality of life, a more
cost-efficient healthcare system and a more inclusive
access to healthcare both in developing countries and
in remote areas in developed countries.
Novel Bio-ICT technologies are needed to achieve
these targets and BISG is active in this area in many
fronts summarised below.
By tracking health status of large groups and including
in the analysis a wealth of metrics and parameters,
large amounts of data are generated. On the other hand,
by downscaling biology-based technologies down to
the nanoscale including sensing biological parameters
directly from living cells, potential security threats are
correspondingly moving into human bodies, but prom-
ising tools are offered for personalised medicine and
treatments, including tight biological interaction, pros-
theses and their control (Celentano and Röning 2015).
BISG is strong in all these areas (data analysis, security
and robotics) and it is therefore pushing itself among
the world leaders in this growingly important area.
0
Healthy state
1
Degeneration starts,
no noticeable impact
on everyday life
2
Mild impacts on
everyday life
3
Disturbs appear
evident or important
4
Severe degeneration
D
Death (complications,
accidents, suicide)
C
Daily care needed
B
Assistance needed
A
Normal life (almost)
preserved
D
Medical
Doctor
H
Hospital
Active
H
osp
ita
lise
d
Cost-
eff
ective
E
xp
ensiv
e
Figure 41 Progress of a disease (left), outcome (right) and access to healthcare (Celentano and Röning 2015).
Towards a Holistic Self-awareness in Humans and AI
Artificial entities like robots and unmanned or autono-
mous vehicles are more and more present in the human
environment. Social interaction among all the players
in such a heterogeneous scenario (Figure 42) calls for a
number of research issues to be addressed and its study
offers interesting potentialities.
Figure 42. Interwork among heterogeneous agents and within them. From Celentano & Röning (2016b).
Self agency. Self-awareness in humans plays a role in a
number of brain functions and disturbances. On the
other hand, self-awareness improves the efficiency in
robotic systems (Celentano and Röning 2016a).
Awareness of the self is achieved through analysis of
observations, or measurements, of various entities
involved. This interwork in a heterogeneous multi-
agent system (Figure 42) may occur with different
topologies: sensing the actuation of other entities, as in
Figure 43a; acquiring information shared by others, as
in Figure 43b; exploiting different functions for
self/nonself discrimination. In short, through perrcep-
tion, action, and sharing information (Celentano &
Röning 2016a).
Figure 43. a) Left: An entity (bottom) sensing the actua-tion of two entities (top). b) Right: Entities (bottom) acquiring instructions shared by another entity (top). From Celentano & Röning (2016a).
Embodied agent. As psychologist James Gibson ob-
served, there is an interdependency of perception and
action (“perceive to act, act to perceive”). We study the
social intelligent entity as embodied (Celentano &
Röning 2016b), where are brought to evidence not only
the interaction among entities but also the interwork
within them (cf. Figure 42 and Figure 44).
Considering that an instantiation of the agent may
possess only part of its functions, the same generic
model can be used at different scales, applied to enti-
ties, at brain, body and world domains (the latter possi-
bly including other entities or agents), benefitting
modularity and scalability (Celentano & Röning
2016b).
INFOTECH OULU Annual Report 2016 20
Figure 44 The embodied agent and its environment. From Celentano & Röning (2016b).
Structured information representation and instruction
logic. Interwork among modular agents include as seen
perception and action but also the exchange of infor-
mation or commands, both referred to as instructions as
in Celentano & Röning (2016a). These communica-
tions may be subject to noise, as it is the case in an
operating room or in air traffic control (Figure 45, top).
Whereas machines are subject to environmental noise
only, humans suffer both environmental noise and
cognitive noise (Celentano & Röning 2016c), affecting
different steps of the information communication pro-
cess (Figure 45, bottom).
decodingencoding
interpretation mapping transfer mapping interpretation
cognitive noise
environmental noise
Figure 45. Top: Interaction among heterogeneous agents in a noisy environment. Bottom: Information communication between remote source and destination entities in noisy conditions. From Celentano & Röning (2016c).
For reliable information exchange among heterogene-
ous agents is needed a formal representation of the
exchanged instructions, usable by both humans and
machines (Figure 46).
Unambiguous
Language
Formal
Representation
Human
Robot
ImplementationMappingInterpretation
Atomi
ROSMSDL
higher level lower level
Human
Robot
Elements
Definitions
BML
Figure 46 Interaction through specified processes (lan-guages and representation). From Celentano & Röning (2016c).
Using the instruction logic in Celentano & Röning
(2016c), the example situation in which mobile m0 at
x0 orders mobile m3 to be in x1 at t1 to search a book b
and bring it immediately to m0 can be represented by
«report_to,m3,m0,x0,t,1»
«move_to,m3,-,x1,t<t1,1»
«search,m3,b,-,t,1»
«bring,m3,b,x0,0,1».
Exploitation of Results
BISG continued co-operation with the SpAtial, Motor
& Bodily Awareness (SAMBA) research group
[http://dippsicologia.campusnet.unito.it/do/gruppi.pl/Sh
ow?_id=hhuv] at the Department of Psychology of the
University of Turin, Italy. Several initiatives for EU
projects including Horizon 2020 are ongoing and these
efforts will be continued.
Outside Europe, BISG is currently co-operating with
the University of Nevada, Arizona State University and
Carnegie Mellon University.
The results of our research were applied to real-world
problems in many projects, often in collaboration with
industrial and other partners. Efficient exploitation of
results is one of the core objectives of the national
Digile and FIMEC ICT SHOK projects like SIMP, IoT
and Cyber Trust; in these projects we work in close
collaboration with companies throughout the projects.
During the reporting year, the group continued utilizing
outdoor robotic systems. Development and utilization
of Mörri, a multipurpose, high performance robot plat-
form continued. More focus was put on perception in
natural conditions, representation of detections,
knowledge, and an environment model of the operating
environment. The software architecture further devel-
oped the earlier work on Property Service Architecture,
and the Marker concept as general purpose representa-
tion was further developed.
INFOTECH OULU Annual Report 2016 21
Future Goals
The partnership in the SIMP programme that belongs
to the SHOK concept of Tekes enables us to continue
our steel research into new areas. The new goals are in
quality prediction at different process stages and for
more challenging properties. As a result more ad-
vanced expert systems can be developed to aid the
operators with different roles in steel making.
We will continue to strengthen our long term research
and researcher training. We will also continuously seek
opportunities for the exploitation of our research results
by collaborating with partners from industry and other
research institutions on national and international re-
search programs and projects. The University of Oulu
is a founding member of euRobotics. Juha Röning is a
member of the Board of Directors of euRobotics.
We will strengthen our international research co-
operation. With the University of Tianjin in China, we
have a joint project in which methods and a system will
be developed for vision-based navigation of Autono-
mous Ground Vehicles, which utilize an omni-
directional camera system as the vision sensor. The aim
is to provide a robust platform that can be utilized in
both indoor and outdoor AGV (Autonomous Ground
Vehicles) applications. This co-operation will continue.
In the USA, we will continue to co-operate with the
Human-Computer Interaction Institute in Carnegie
Mellon University with Assistant Professor Anind K.
Dey. The research is on human modelling in the area of
human-machine interaction. We continue and strength-
en US-Finland co-operation through an NSF grants.
The co-operation within SOCRATE co-operation with
the University of Nevada can be exploited complemen-
tary expertise in the area of multi-layer security. Two
new BISG project proposals for co-operative projects
under the WiFiUS programme are currently under
review at the Academy of Finland and NSF.
Shorter research visits to European partners in EU-
funded projects are also planned. The cooperation with
Prof. Raffaella Ricci and her colleagues, focuses on
bridging neuroscience and artificial intelligence. This
research aims at cross-fertilising the two scientific
domains, continuing and strengthening the research
paths currently active at respective sides.
In 2017, the aim is to utilize more widely the know-
how from sensor technology and data mining. New
application areas will be studied, including rehabilita-
tion, exercise motivation and energy efficiency in
households, and the benefits of our expertise will be
highlighted to actors in the areas.
In human-environment interaction and sensor net-
works, our research will continue. Our main goals are
to develop analysis methods for sensor network data
and to develop applications utilizing physical user
interfaces. Research on novel software architectures,
reasoning and knowledge representations will continue
as well. Field trials in realistic settings, and close col-
laboration with research groups (national and interna-
tional) and companies will be emphasized.
Personnel
professors 2
senior research fellows
postdoctoral researchers 10
doctoral students 15
other research staff 5
total 32
person years for research 25
External Funding
Source EUR
Academy of Finland 156 000
Tekes 735 000
domestic private 176 000
international 200 000
total 1 267 000
Doctoral Theses
Latvakoski, Juhani (2016) Small world for dynamic
wireless cyber-physical systems. VTT Science 142.
Selected Publications
Alasalmi T., Koskimäki H., Suutala J. and Röning J. (2016).
Instance level classification confidence estimation. Advances
in Intelligent Systems and Computing. The 13th International
Conference on Distributed Computing and Artificial Intelli-
gence 2016, Springer.
Celentano U (2016) Panel: European Project Space on Intel-
ligent Technologies for Innovation and Sustainability. Invit-
ed. 8th International Conference on Agents and Artificial
Intelligence (ICAART). 24–26 Feb 2016, Rome, Italy.
Celentano U, Röning J (2016a) Multi-robot systems, ma-
chine-machine and human-machine interaction, and their
modelling. 8th International Conference on Agents and Arti-
ficial Intelligence (ICAART), vol. 1, pp. 118–125. 24–26
Feb, Rome, Italy.
Celentano U, Röning J (2016b) Modular agents for heteroge-
neous human-robot systems. ERL Emergency & TRADR
Workshop on Heterogeneity in Robotic Systems, Oulu, Fin-
land, 22–26 Aug.
Celentano U, Röning J (2016c) Structured information repre-
sentation and exchange in heterogeneous multi-agent systems
in mission-critical scenarios. Information Systems Technolo-
gy Panel: Specialists Meeting on Intelligence & Autonomy
(Ro-botics). Bonn, Germany, 25–27 Oct.
Celentano U, Röning J, Yang L, Zhang J, Ermolova N, Tirk-
konen O, Chen T, Höyhtyä M (manuscript) Information and
physical security in people-centric IoT.
Höyhtyä M, Mämmelä A, Celentano U, Röning J (2016)
Power-efficiency in social-aware D2D communications.
Proc. European Wireless Conference (EW 2016). Oulu,
Finland, 18–20 May 2016.
INFOTECH OULU Annual Report 2016 22
Koskimäki H and Siirtola P (2016) Recognizing Unseen Gym
Activities from Streaming Data - Accelerometer vs. Electro-
myogram Advances in Intelligent Systems and Computing,
International Conference on Distributed Computing and
Artificial Intelligence
Koskimäki H and Siirtola P (2016) Adaptive Model Fusion
for Wearable Sensors Based Human Activity Recognition
International Conference on Information Fusion, ISIF, 07,
1709-1713.
Koskimäki H and Siirtola P (2016) Model Update in Weara-
ble Sensors Based Human Activity Recognition IEEE Sym-
posium on Computational Intelligence and Data Mining,
accepted.
Tuovinen L (2016) A conceptual model of actors and interac-
tions for the knowledge discovery process. In Proc. 8th Inter-
national Joint Conference on Knowledge Discovery,
Knowledge Engineering and Knowledge Management –
Volume 1: KDIR, 240–248.
Tuovinen L, Ahola R, Kangas M, Korpelainen R, Siirtola P,
Luoto T, Pyky R, Röning J & Jämsä T (2016) Software de-
sign principles for digital behavior change interventions:
Lessons learned from the MOPO study. In Proc. 9th Interna-
tional Conference on Biomedical Engineering Systems and
Technologies – Volume 5: HEALTHINF, 175–182.
Niemelä Maisa, Ahola Riikka, Pyky Riitta, Jauho Anna-
Maiju, Tuovinen Lauri, Siirtola Pekka, Tornberg Jaakko,
Mäntysaari Matti, Keinänen-Kiukaanniemi Sirkka, Röning
Juha, Jämsä Timo, Korpelainen Raija (2016) Nuorten miesten
fyysinen aktiivisuus ja istuminen itsearvioituna ja mitattuna
Liikunta & Tiede, 53(2-3):73-79.
Pietikäinen P, Kettunen A & Röning, J (2016) Steps Towards
Fuzz Testing in Agile Test Automation. International Journal
of Secure Software Engineering, Volume 7 Issue 1, January
2016, pp. 38-52.
Siirtola P & Röning J (2016) Reducing Uncertainty in User-
independent Activity Recognition - a Sensor Fusion-based
Approach International Conference on Pattern Recognition
Applications and Methods, Rome, Italy 24-26 February 2016,
611--619.
Siirtola P, Koskimäki H & Röning J (2016) From User-
independent to Personal Human Activity Recognition Models
Exploiting the Sensors of a Smartphone 24th European Sym-
posium on Artificial Neural Networks, Computational Intelli-
gence and Machine Learning, ESANN 2016., Bruges, Bel-
gium 27-29 April 2016, 471--476.
Siirtola P, Koskimäki H & Röning J (2016) Personal models
for eHealth - improving user-dependent human activity
recognition models using noise injection IEEE Symposium
on Computational Intelligence and Data Mining, December,
accepted.
Siirtola P.; Tamminen S.; Ferreira E.; Tiensuu H.; Prokkola
E.; Röning J. (2016) Automatic Recognition of Steel Plate
Side Edge Shape Using Classification and Regression Models
The 9th Eurosim Congress on Modelling and Simulation,
September.
Tiensuu H, Tamminen S, Pikkuaho A & Röning J (2016)
Improving the yield of steel plates by updating the slab de-
sign with statistical models. Ironmaking and Steelmaking:
Processes, Products and Applications, accepted, August
2016.
Tuovinen L, Ahola R, Kangas M, Korpelainen R, Siirtola P,
Luoto T, Pyky R, Röning J, Jämsä T (2016) Software Design
Principles for Digital Behavior Change Interventions: Les-
sons Learned from the MOPO Study Proceedings of the 9th
International Joint Conference on Biomedical Engineering
Systems and Technologies - Volume 5: HEALTHINF, 175-
182.
Drelon C, Berthon A, Sahut-Barnola I, Mathieu M, Dumontet
T, Rodriguez S, Batisse-Lignier M, Tabbal H, Tauveron I,
Lefrançois-Martinez AM, Pointud JC, Gomez-Sanchez CE,
Vainio S, Shan J, Sacco S, Schedl A, Stratakis CA, Martinez
A, Val P. PKA inhibits WNT signalling in adrenal cortex
zonation and prevents malignant tumour development. Nat
Commun. 2016 Sep 14;7:12751. doi:10.1038/ncomms12751.
PubMed PMID: 27624192; PubMed Central PMCID:
PMC5027289.
Nagy II, Xu Q, Naillat F, Ali N, Miinalainen I, Samoylenko
A, Vainio SJ. Impairment of Wnt11 function leads to kidney
tubular abnormalities and secondary glomerular cystogene-
sis. BMC Dev Biol. 2016 Aug 31;16(1):30. doi:
10.1186/s12861-016-0131-z. PubMed PMID: 27582005;
PubMed Central PMCID:PMC5007805.
Rak-Raszewska A, Vainio S. Nephrogenesis in organoids to
develop novel drugs and progenitor cell based therapies. Eur
J Pharmacol. 2016 Nov 5;790:3-11.
doi:10.1016/j.ejphar.2016.07.011. PubMed PMID: 27395798.
Xu Q, Krause M, Samoylenko A, Vainio S. Wnt Signaling in
Renal Cell Carcinoma. Cancers (Basel). 2016 Jun 17;8(6).
pii: E57. doi: 10.3390/cancers8060057. Review. PubMed
PMID: 27322325; PubMed Central PMCID: PMC4931622.
Vidal V, Sacco S, Rocha AS, da Silva F, Panzolini C,
Dumontet T, Doan TM, Shan J, Rak-Raszewska A, Bird T,
Vainio S, Martinez A, Schedl A. The adrenal capsule is a
signaling center controlling cell renewal and zonation
through Rspo3. Genes Dev. 2016 Jun 15;30(12):1389-94.
doi: 10.1101/gad.277756.116. PubMed PMID: 27313319;
PubMed Central PMCID: PMC4926862.
Halt KJ, Pärssinen HE, Junttila SM, Saarela U, Sims-Lucas
S, Koivunen P, Myllyharju J, Quaggin S, Skovorodkin IN,
Vainio SJ. CD146(+) cells are essential for kidney vascula-
ture development. Kidney Int. 2016 Aug;90(2):311-24. doi:
10.1016/j.kint.2016.02.021. PubMed PMID: 27165833.
Pietilä I, Prunskaite-Hyyryläinen R, Kaisto S, Tika E, van
Eerde AM, Salo AM, Garma L, Miinalainen I, Feitz WF,
Bongers EM, Juffer A, Knoers NV, Renkema KY, Myllyhar-
ju J, Vainio SJ. Wnt5a Deficiency Leads to Anomalies in
Ureteric Tree Development, Tubular Epithelial Cell Organi-
zation and Basement Membrane Integrity Pointing to a Role
in Kidney Collecting Duct Patterning. PLoS One. 2016 Jan
21;11(1):e0147171. doi: 10.1371/journal.pone.0147171.
PubMed PMID: 26794322; PubMed Central PMCID:
PMC4721645.
Prunskaite-Hyyryläinen R, Skovorodkin I, Xu Q, Miinalainen
I, Shan J, Vainio SJ. Wnt4 coordinates directional cell migra-
tion and extension of the Müllerian duct essential for onto-
genesis of the female reproductive tract. Hum Mol Genet.
2016 Mar 15;25(6):1059-73. doi: 10.1093/hmg/ddv621.
PubMed PMID: 26721931; PubMed Central PMCID:
PMC4764189.
Krause M, Samoylenko A, Vainio SJ. Exosomes as renal
inductive signals in health and disease, and their application
as diagnostic markers and therapeutic agents. Front Cell Dev
Biol. 2015 Oct 20;3:65. doi: 10.3389/fcell.2015.00065. Re-
view. PubMed PMID: 26539435; PubMed Central PMCID:
PMC4611857.
Daniel E, Onwukwe GU, Wierenga RK, Quaggin SE, Vainio
SJ, Krause M. ATGme: Open-source web application for rare
INFOTECH OULU Annual Report 2016 23
codon identification and custom DNA sequence optimization.
BMC Bioinformatics. 2015 Sep 21;16:303. doi:
10.1186/s12859-015-0743-5. PubMed PMID: 26391121;
PubMed Central PMCID: PMC4578782.
Bibikova O, Popov A, Bykov A, Prilepskii A, Kinnunen M,
Kordas K, Bogatyrev V, Khlebtsov N, Vainio S, Tuchin V.
Optical properties of plasmon-resonant bare and silica-coated
nanostars used for cell imaging. J Biomed Opt. 2015
Jul;20(7):76017. doi: 10.1117/1.JBO.20.7.076017. PubMed
PMID: 26230637.
Rak-Raszewska A, Hauser PV, Vainio S. Organ In Vitro
Culture: What Have We Learned about Early Kidney Devel-
opment? Stem Cells Int. 2015;2015:959807. doi:
10.1155/2015/959807. Review. PubMed PMID: 26078765;
PubMed Central PMCID: PMC4452498.
Berry RL, Ozdemir DD, Aronow B, Lindström NO, Dudna-
kova T, Thornburn A, Perry P, Baldock R, Armit C, Joshi A,
Jeanpierre C, Shan J, Vainio S, Baily J, Brownstein D, Da-
vies J, Hastie ND, Hohenstein P. Deducing the stage of origin
of Wilms' tumours from a developmental series of Wt1-
mutant mice. Dis Model Mech. 2015 Aug 1;8(8):903-17. doi:
10.1242/dmm.018523. PubMed PMID: 26035382; PubMed
Central PMCID: PMC4527280.
Ali N, Hosseini M, Vainio S, Taïeb A, Cario-André M, Rez-
vani HR. Skin equivalents: skin from reconstructions as
models to study skin development and diseases. Br J Derma-
tol. 2015 Aug;173(2):391-403. doi: 10.1111/bjd.13886. Re-
view. PubMed PMID: 25939812.
Krause M, Rak-Raszewska A, Pietilä I, Quaggin SE, Vainio
S. Signaling during Kidney Development. Cells. 2015 Apr
10;4(2):112-32. doi: 10.3390/cells4020112. Review. PubMed
PMID: 25867084; PubMed Central PMCID: PMC4493451.
Naillat F, Yan W, Karjalainen R, Liakhovitskaia A,
Samoylenko A, Xu Q, Sun Z, Shen B, Medvinsky A, Quag-
gin S, Vainio SJ. Identification of the genes regulated by
Wnt-4, a critical signal for commitment of the ovary. Exp
Cell Res. 2015 Mar 15;332(2):163-78. doi:
10.1016/j.yexcr.2015.01.010. PubMed PMID: 25645944.
Rajaram RD, Buric D, Caikovski M, Ayyanan A, Rougemont
J, Shan J, Vainio SJ, Yalcin-Ozuysal O, Brisken C. Proges-
terone and Wnt4 control mammary stem cells via myoepithe-
lial crosstalk. EMBO J. 2015 Mar 4;34(5):641-52. doi:
10.15252/embj.201490434. PubMed PMID: 25603931;
PubMed Central PMCID: PMC4365033.
Junttila S, Saarela U, Halt K, Manninen A, Pärssinen H,
Lecca MR, Brändli AW, Sims-Lucas S, Skovorodkin I, Vain-
io SJ. Functional genetic targeting of embryonic kidney
progenitor cells ex vivo. J Am Soc Nephrol. 2015
May;26(5):1126-37. doi: 10.1681/ASN.2013060584. Pub-
Med PMID: 25201883; PubMed Central PMCID:
PMC4413750.
Naillat F, Veikkolainen V, Miinalainen I, Sipilä P, Poutanen
M, Elenius K, Vainio SJ. ErbB4, a receptor tyrosine kinase,
coordinates organization of the seminiferous tubules in the
developing testis. Mol Endocrinol. 2014 Sep;28(9):1534-46.
doi: 10.1210/me.2013-1244. PubMed PMID: 25058600.
Rymer C, Paredes J, Halt K, Schaefer C, Wiersch J, Zhang G,
Potoka D, Vainio S, Gittes GK, Bates CM, Sims-Lucas S.
Renal blood flow and oxygenation drive nephron progenitor
differentiation. Am J Physiol Renal Physiol. 2014 Aug
1;307(3):F337-45. doi: 10.1152/ajprenal.00208.2014. Pub-
Med PMID: 24920757; PubMed Central PMCID:
PMC4121567.
Maezawa Y, Onay T, Scott RP, Keir LS, Dimke H, Li C,
Eremina V, Maezawa Y, Jeansson M, Shan J, Binnie M,
Lewin M, Ghosh A, Miner JH, Vainio SJ, Quaggin SE. Loss
of the podocyte-expressed transcription factor Tcf21/Pod1
results in podocyte differentiation defects and FSGS. J Am
Soc Nephrol. 2014 Nov;25(11):2459-70. doi:
10.1681/ASN.2013121307. PubMed PMID: 24904088;
PubMed Central PMCID: PMC4214535.
Pietilä I, Vainio SJ. Kidney development: an overview.
Nephron Exp Nephrol. 2014;126(2):40. doi:
10.1159/000360659. Review. PubMed PMID: 24854638.
Halt K, Vainio S. Coordination of kidney organogenesis by
Wnt signaling. Pediatr Nephrol. 2014 Apr;29(4):737-44. doi:
10.1007/s00467-013-2733-z. Review. PubMed PMID:
24445433; PubMed Central PMCID: PMC3928513.
Prunskaite-Hyyryläinen R, Shan J, Railo A, Heinonen KM,
Miinalainen I, Yan W, Shen B, Perreault C, Vainio SJ. Wnt4,
a pleiotropic signal for controlling cell polarity, basement
membrane integrity, and antimüllerian hormone expression
during oocyte maturation in the female follicle. FASEB J.
2014 Apr;28(4):1568-81. doi: 10.1096/fj.13-233247. PubMed
PMID: 24371124.
Cheddad A, Nord C, Hörnblad A, Prunskaite-Hyyryläinen R,
Eriksson M, Georgsson F, Vainio SJ, Ahlgren U. Improving
signal detection in emission optical projection tomography
via single source multi-exposure image fusion. Opt Express.
2013 Jul 15;21(14):16584-604. doi: 10.1364/OE.21.016584.
PubMed PMID: 23938510.